Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/hkuds/openspace/docx-shell-parse-enhancednpx skills add HKUDS/OpenSpace --skill docx-shell-parse-enhancedgit clone --depth 1 https://github.com/HKUDS/OpenSpaceWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00026 | $0.01895 |
| Opus 5 | $0.00013 | $0.00948 |
| Sonnet 5 | $0.00005 | $0.00379 |
| Haiku 4.5 | $0.00003 | $0.00189 |
Grade A, and why
docx-parse-resilient scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run( How it starts
The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resilient DOCX Text Extraction
Extract text from Microsoft Word (.docx) files using a robust two-tier approach: shell-based extraction as the primary method, with Python zipfile fallback when shell commands fail or return no output.
When to Use
- Python environment may lack
python-docxbutzipfilemodule is available (standard library) - Working in constrained or inconsistent environments (containers, minimal images, CI/CD)
- Shell
unzipcommand returns errors or no output - Need reliable extraction with automatic fallback
Core Technique
DOCX files are ZIP archives containing XML files. This skill provides two extraction methods:
- Primary (Shell):
unzip -p+sedfor fast extraction - Fallback (Python):
zipfilemodule for reliable extraction when shell fails
Step-by-Step Instructions
1. Verify the DOCX file exists
ls -la document.docx
2. Test shell extraction first (recommended)
Try the shell-based approach:
unzip -p document.docx word/document.xml 2>/dev/null | sed -e 's/<[^>]*>//g'
3. Check if shell extraction produced output
Verify the shell method returned content:
content=$(unzip -p document.docx word/document.xml 2>/dev/null | sed -e 's/<[^>]*>//g')
if [ -z "$content" ]; then
echo "Shell extraction returned no output, trying Python fallback..."
fi
4. Use Python zipfile fallback if needed
When shell commands fail or return empty output, use Python's standard zipfile module:
python3 -c "
import zipfile
import sys
import re
try:
with zipfile.ZipFile('document.docx', 'r') as z:
content = z.read('word/document.xml').decode('utf-8')
# Strip XML tags
text = re.sub(r'<[^>]*>', '', content)
# Clean whitespace
lines = [line.strip() for line in text.split('\n') if line.strip()]
print('\n'.join(lines))
except Exception as e:
print(f'Error: {e}', file=sys.stderr)
sys.exit(1)
"
5. Save extracted text to file
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 264 lines · 26 tokens per session scan A c23ca6e7b740
docx-parse-resilient is a skill published in the GitHub repository HKUDS/OpenSpace (7,486 stars, last pushed 21d ago), licensed MIT. It adds 26 tokens to every session and 1,895 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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